© 2012 IBM Corporation

ed il LEAN IT

Evento CUOA sul LEAN ITAltavilla Vicentina, 20 Novembre 2012

Fabrizio Renzi, Direttore Tecnico IBM Italia

Fabrizio_renzi@it.ibm.com

© 2012 IBM Corporation2

Gli studi IBM confermano il bisogno del miglioramento continuo (lean)

1. Companies must become more client centric by leveraging sophisticated insights

2. Extensive partnering is enabling CEOs to make radical innovation. Source: IBM’s 2012

CEO Survey, 1,700 CEO’s

CMO’s top concerns:1.Data Explosion2.Social Media3.Growth of channel

choices4.Shifting demographics

CIO’s top focus:

1. Insight & Intelligence

2.Client Intimacy

3.Virtualization

4.Cloud Computing

*Source: Top 200 global bank survey, IBM Institute for Business Value, The Economist Intelligence Unit.

© 2012 IBM Corporation3

Standardization enabled by

integrated service management

Lower IT Operating and Capital Costs

Capex to Opex

Fast access to current technology

and powerful computing

Removing IT complexity from

end users

Fine grained IT services with rapid

provisioning

Che cosa ci chiedono nostri clienti per l’IT: (lean)Cost Savings + Innovation = Value Creation

© 2012 IBM Corporation4

La visione IBM per l’ICT nel 2012.

Smarter Planet

Analytics& Big data

CloudComputing

New technologies

Social & Mobile

� Oltre 3.200 ricercatori e

scienziati

� 5 premi Nobel � Da 18 anni prima società

negli Stati Uniti per

numero di brevetti(circa 53.000 in 18 anni,

5.896 nel 2010)

Spese annuali in:� R&D 6 B$

� Acquisizioni sfw 6-10 B$

� New technologies investment. 5-8 B$

IBM a supportodell’innovazione con R&D e acquisizioni

© 2012 IBM Corporation5

Analytics sono definiti come l’uso dei dati e del calcolo per AIUTARE a prendere decisioni smart. Sono sempre più usati per le aree dellagestione del rischio, payments, CRM, interactive marketing, couponing, trading, finance, strategic planning….…..

Data

Historical

Simulated

Text Video, Images Audio

� Data instances

� Reports and queries on data aggregates

� Predictive models

� Answers and confidence

� Feedback and learning

Decision point Possible outcomes

Option 1

Option 2

Option 3

5

© 2012 IBM Corporation6 6

* Truthfulness, accuracy or precision, correctness

La 4 dimensione dei Big Data l’affidabilità del dato.

Volume Velocity Veracity*Variety

Data at Rest

Terabytes to exabytes of existing

data to process

Data in Motion

Streaming data, milliseconds to

seconds to respond

Data in Many Forms

Structured, unstructured, text,

multimedia

Data in Doubt

Uncertainty due to data inconsistency& incompleteness,

ambiguities, latency, deception, model approximations

© 2012 IBM Corporation7

Esempio di condensation sui dati da google. (carrots 2) Risultato ricerca con online 13/11/2012: Per IBM RENZI FABRIZIO TECHNICAL DIRECTOR

Condensare i dati costruisce un contesto attorno agli stessi